Prof. Thomas Canhao Xu
BNU-HKBU United International College
Circular Economy, Leadership
Speech Title: Hardware/Software Codesign of Efficient Deep Learning Algorithms
Abstract: The efficiency of machine learning and deep learning algorithms is more and more important nowadays. Improving accuracy without considering model efficiency is undesirable. Deep learning algorithms on embedded devices, such as educational devices and/or educational robots, often have demanding real-time requirements. For example, object recognition systems based on cameras usually require a latency of hundreds of milliseconds to respond to events in a timely manner. Commercial embedded devices sometimes offload the machine learning algorithms to the cloud. However, network connection quality and speed are becoming another challenging constraint for these devices. Another choice is to implement a high efficient deep learning algorithm on the embedded device, which isn’t affected by the internet connection. Enabling deep learning on the embedded device is difficult. The main characteristic of embedded devices is low power, which usually means the limited computational capability of the processor and limited size of the memory. From the perspective of software/hardware codesign, in order to speed up the processing speed of deep learning and image recognition algorithms, optimizations at both the algorithmic and hardware-level are required.
Prof. Ying Yang
Professor, Ph.D., master supervisor, graduated from Beijing University of Aeronautics and Astronautics with a bachelor's degree in electronic information engineering in 1991. In 1996, She graduated from Guangxi University with a master's degree in automatic control. She graduated from the School of Information of Donghua University in 2006 with a doctorate degree. From January to May 2010, she went to the University of Vermont in the United States as a visiting scholar. Post-doctorate from Fudan University in 2013.
Presided over and mainly participated in 20 national, provincial and ministerial scientific research projects, presided over 1 national SME innovation project, mainly participated in 1 National Natural Science Foundation project, presided over the Guangxi Natural Science Foundation project << OGSA-based distributed flow in P2P environment Research on data query processing>> etc. 2 items, presided over the Guangxi Education Department project <<Research on the Component-based Union Resource Plan (URP)>>, presided over 3 science fund projects of Guangxi University, mainly participated in 1 National Natural Science Foundation of China , Guangxi Science and Technology Research Project <<Information Management and Analysis System for Patients with Chronic Multiple Diseases>>, <<Key Application Demonstration of Logistics Informatization for Modern Business Chain Enterprises>>, <<Free Handwritten Digital Form Automatic Recognition System>> and other five items, Mainly participated in the Guangxi Department of Health project "Development and Application of Information Management and Analysis System for Patients with Chronic Viral Hepatitis", and mainly participated in 5 scientific and technological projects in Nanning.
SCHOOL OF C.S. OF XUT
Dr. Wei Wei is an associate professor of School of Computer Science and Engineering，Xi'an University of Technology, Xi'an 710048, China. He is a senior member of IEEE, CCF. He received his Ph.D. and M.S. degrees from Xi'an Jiaotong University in 2011 and 2005, respectively. He ran many funded research projects as principal investigator and technical members. His research interest is in the area of wireless networks, wireless sensor networks Application, Image Processing, Mobile Computing, Distributed Computing, and Pervasive Computing, Internet of Things, Sensor Data Clouds, etc. He has published around one hundred research papers in international conferences and journals. He is an editorial board member of FGCS, IEEE Access, AHSWN, IEICE, KSII, etc. He is a TPC member of many conferences and regular reviewer of IEEE TPDS, TVT, TIP, TMC, TWC, JNCA and many other Elsevier journals.
|Dr. Sandeep Saxena|
Galgotias College of Engineering and Technology, Greater Noida, India.
Cloud Computing, Information Security, Blockchain Technology
Speech Title: Vulnerability Assessment (Topic of Cyber Security)
Abstract: Vulnerability Assessment (VA) is the process of identifying technical vulnerabilities in computers and networks as well as weaknesses in policies and practices relating to the operation of the systems. It evaluates if the system is susceptible to any known vulnerabilities, assigns severity levels to those vulnerabilities, and recommends remediation or mitigation, if and whenever needed. We have to establish the security baseline before starting the process of vulnerability assessment. Administrative support is the key to perform the vulnerability assessment in the system.